Quantifying relationships in natural systems

Analysis of large-scale patterns in species’ and community traits over time and space and relationships to drivers may be important to identifying and understanding issues beyond the scope of empirical studies. Analysis of natural communities, especially hyper-diverse ones that are difficult to recreate, is also essential for understanding the true impacts of diversity. The recent and rapid increases in available data
and developments in statistics and computing power allow these patterns to be
identified and analyzed. Our projects focus on considering how to define and quantify drivers, diversity, and impacts and using these relationships to test hypotheses
derived from experiments concerning the formation and impacts of diversity on a broader
scale. Current projects include:

Drivers of diversity and ecosystem services in hyperdiverse systems

Hyperdiverse communities such as kelp forests and tropical forests offer excellent chances to test hypotheses formed in experimental systems and are the focus of current work in the lab exploring how we define diversity and why it matters. Working with DBDGS and the TEAM network, we characterized taxonomic and functional diversity in tropical forests around the world, considered drivers of diversity at various levels, and related diversity to ecosystem services such as carbon storage. The lab is continuing to develop projects focused on these tropical forest sites. Using long-term data collected by scientists at the Marine Science Institute at the University of California, we are also studying how we define diversity in kelp forests, what drives it, and how that should impact monitoring programs for marine protected areas.

Analysis of diversity in the Gulf of Mexico

As part of the Deep-C consortium investigating impacts of the Deepwater Horizon oil spill, we are integrating data on food webs, oceanographic processes, oil degradation, and human uses of the environment into an end-to-end Atlantis ecosystem model for the eastern Gulf of Mexico. This model will allow scientists to simulate long-term community responses to multiple stressors, increasing our understanding of how local changes impact long-term populaton dynamics on a regional scale. We are also developing new open source tools (usually via R packages) to enable ecosystem models to be more easily constructed, calibrated, assessed, and compared.

Gosnell,
J. S. A more efficient route to Atlantis: new tools for developing and
comparing Atlantis models applied to new models for the eastern Gulf of
Mexico. Poster presentation for the 2014 Gulf of
Mexico Oil Spill and Ecosystem Conference.